title: Versioning computer-interpretable guidelines: semi-automatic modeling of 'Living Guidelines' using an information extraction method.
abstract: OBJECTIVE
  Clinical practice guidelines (CPGs) are means to provide evidence-based medical knowledge. In order to make up-to-date "best" scientific evidence available these documents need to be updated on an ongoing basis. An effective method to accomplish this aim is offered by the so-called "living guidelines": Living guidelines are documents presenting up-to-date and state-of-the-art knowledge to practitioners. To have guidelines implemented by computer-support they have to be formalized in a computer-interpretable form in a first step. Due to the complexity of such formats the formalization process is burdensome and time-consuming. Automating parts of the modeling process and, consequently, modeling updates of these guideline documents are demanded.
  
  
  METHODS
  The LASSIE methodology supports this task by formalizing guidelines in several steps from the textual form to the guideline representation language Asbru using a document-centric approach. LASSIE uses information extraction techniques to semi-automatically accomplish these steps. We apply LASSIE to support the implementation of living guidelines.
  
  
  RESULTS
  Based on a living guideline published by the Scottish Intercollegiate Guidelines Network (SIGN) we show that adaptations of previously formalized guidelines can be accomplished easily and fast. Thereby, the different versions of guideline documents are compared and updates are identified. Due to the traceable formalization method of linking text parts and their corresponding formal models, we are able to inherit unchanged models from previously formalized versions. Thus, we only need to formalize updated text parts using the semi-automatic formalization method LASSIE.
  
  
  CONCLUSIONS
  We propose a simple, time-saving, but effective method called LASSIE to formalize new guideline versions of previously formalized CPGs. Furthermore, models that have been added or modified by knowledge engineers in previous versions can also be transferred easily. This will result in a faster implementation of new guideline versions also known as living guidelines to provide up-to-date knowledge necessary for accomplishing the daily work of health care professionals.
authors.affiliation: Vienna University of Technology, Institute of Software Technology & Interactive Systems, Favoritenstrasse 9-11/188, A-1040 Vienna, Austria. kaiser@ifs.tuwien.ac.at
authors.forename: Katharina
authors.initials: K
authors.lastname: Kaiser
authors.forename: Silvia
authors.initials: S
authors.lastname: Miksch
mesh_terms: D001185:Artificial Intelligence; D001249:Asthma / Q000628:therapy*; D001331:Automation; D020000:Decision Support Systems, Clinical; D019317:Evidence-Based Medicine; D019983:Guideline Adherence; D006801:Humans; D008962:Models, Theoretical; D017410:Practice Guidelines as Topic; D011381:Programming Languages; D018511:Systems Integration; D014584:User-Computer Interface